The present invention relates to a method and apparatus for sorting, and more specifically to a method for detecting and identifying a characteristic which may be, but is not limited to, a defect in an agricultural product or object, and then removing the product having the detected and identified characteristic or removing the defect itself, from a moving product stream.
It has long be known that camera images including, line scan cameras are commonly combined with laser scanners or LIDAR and/or time of flight imaging for three dimensional imaging, and surface and subsurface inspection, and which are used to perceive depth, and distance, and to further track moving objects, and the like. Such devices have been employed in sorting apparatuses of various designs in order to identify acceptable and unacceptable objects, or products having detected and identified characteristics, within a stream of products to be sorted, thus allowing the sorting apparatus to remove undesirable objects or products from the stream of products in order to produce a homogeneous product stream which is more useful for food processors, and the like. Heretofore, attempts which have been made to enhance the ability to inspect objects effectively, in real-time, have met with somewhat limited success. In the present application, the term “real-time” when used in this document, relates to information processing which occurs within the span of, and substantially at the same rate, as that which it is depicted. “Real-time” may include several micro-seconds to a few milliseconds.
One of the chief difficulties associated with such efforts has been that when particular radiators, emitters, illuminators, detectors, sensors, and the like have been previously employed, and then energized both individually and, in combination with each other, they have undesirable affects and limitations including, but not limited to, lack of isolation of the signals of different modes, but similar optical spectrum; unwanted changes in the response per optical angle of incidence, and field angle; a severe loss of sensitivity or effective dynamic range of the sensor being employed, (i.e. low signal-to-noise ratio, low signal amplitude) among many others. Thus, the use of multiple sensors or interrogating means for detecting, gathering and providing information regarding the objects being sorted, when actuated, simultaneously, often destructively interfere with each other and thus limit the ability to identify external and internal features or characteristics of an object which would be helpful in classifying the object being inspected into different grades or classifications, or as being either, on the one hand, an acceptable product or object, or on the other hand, an unacceptable product or object, which needs to be excluded/removed from the product stream.
The developers of optical sorting systems which are uniquely adapted for visually inspecting a mass-flow of a given food product have endeavored, through the years, to provide increasing levels of information which are useful in making well-informed sorting decisions to effect sorting operations in mass-flow food sorting devices. While the creation of, capturing and processing of product data, including but not limited to images employing prior art cameras and other optical devices, such as but not limited to laser scanners, have long been known, it has also been recognized that data about, and images of a product formed by visible spectrum electromagnetic radiation often will not provide enough information for an automated sorting machine to accurately identify all (and especially hidden, internal or below surface) defects, and which may subsequently be later identified or develop after further processing of the product. For example, one of the defects in agricultural products which have troubled food processors through the years has been the effective identification of “sugar end” defects in potato products, and more specifically potato products that are destined for processing into food items such as French Fries, potato chips and the like.
Another example of a defect in agricultural products that has troubled food processors through the years has been the detection and/or identification of internal defects, or defects occurring below an external surface in agricultural products, including but not limited to detection of precursors of cancer-causing acrylamide (which is generated in high temperature cooking such as frying) and detection of other internal/below surface characteristics that are indicative of unacceptable items. Such characteristics may include, but are not limited to, the presence of chlorophyll which may be a predictor of the presence of solanine; and the detection of reducing sugars such as, but not limited to fructose and glucose that can react with asparagine to form acrylamide.
Chlorophyll, which is well known as causing the “green color” of plants frequently develops below the peel in potatoes that are exposed to light after harvesting. In small amounts, chlorophyll is not visually perceptible as “green” but the chlorophyll is nevertheless present and can cause the potato/piece of potato to be an unacceptable product. Further still, the presence of chlorophyll has been found to be a predictor of the presence of solanine and chaconine which are glyalkaloid poisons which have pesticide properties and which can cause illness if consumed. It is therefore important to identify potatoes and potato pieces having chlorophyll and to remove such potatoes and potato pieces from the product stream.
One of the primary methods to detect the presence of chlorophyll, which may be internal/below the surface, is through the detection and identification of chlorophyll fluorescence. Chlorophyll fluorescence occurs when chlorophyll is exposed to electromagnetic radiation which energizes the chlorophyll molecules which then emit light in the red and infra-red (IR) color spectrum. The irradiation of plant based products with electromagnetic radiation, including but not limited to ultraviolet radiation, infrared radiation, and electromagnetic excitation, and the detection and identification of emitted electromagnetic radiation and/or fluorescent light provides a method for making a sorting decision based on non-visually perceptible characteristics of the items being sorted. Similarly, the identification of other hidden and/or internal and/or below surface characteristics that are precursors to harmful and/or unacceptable characteristics may similarly be identified or determined by exposing the product stream to electromagnetic radiation of various wavelengths and substantially simultaneously monitoring and detecting emitted or reflected or refracted electromagnetic radiation which is indicative of the particular precursor and/or characteristic.
For example, potato strips or French Fries made from “sugar end” potatoes exhibit or display undesirable dark-brown areas on the product after the potato piece has been subjected to frying. This defect is typically caused by the higher concentration of reducing sugars found in the given darkened region of the potato. The process of frying the product results in caramelizing, which creates the undesirable dark brown region on the fried product. The challenge for food processors has been that the “sugar end” defects are typically invisible to traditional optical detection technology until after the potato product has been cooked. In view of this situation, potato strip and potato chip processors can be unaware they have “sugar end” problems within a given lot of potatoes until downstream food service customers fry the potato strips and chips and then provide complaints.
Those skilled in the art have recognized that a variety of factors can encourage development of such undesirable characteristics. It has further been found that reducing sugars can develop in tubers during cold storage prior to processing and that such reducing sugars may be converted back into sucrose (not a reducing sugar) by environmental conditions such as, but not limited to, warming the tubers to “room temperature” prior to cooking. As such, some of these undesirable characteristics can be difficult to detect and identify.
While the various prior art devices and methodology which have been used, heretofore, have worked with various degree of success, assorted industries such as food processors, and the like, have searched for enhanced means for discriminating between products or objects traveling in a stream so as to produce ever better quality products, or resulting products having different grades, for subsequent supply to various market segments.
A method and apparatus for sorting which avoids the detriments associated with the various prior art teachings, and practices utilized, heretofore, is the subject matter of the present application.